R Notebook

library(reticulate)
use_python("/opt/anaconda3/bin/python")
py_config()

python:         /opt/anaconda3/bin/python
libpython:      /opt/anaconda3/lib/libpython3.6m.so
pythonhome:     /opt/anaconda3:/opt/anaconda3
version:        3.6.5 |Anaconda, Inc.| (default, Apr 29 2018, 16:14:56)  [GCC 7.2.0]
numpy:          /opt/anaconda3/lib/python3.6/site-packages/numpy
numpy_version:  1.14.3

python versions found: 
 /opt/anaconda3/bin/python
 /usr/bin/python
 /usr/bin/python3
 /home/clint/.virtualenvs/r-tensorflow/bin/python
 /home/clint/plaidml/bin/python

##############################################################
import numpy as np
import pandas as pd
import os, re
import matplotlib.pyplot as plt

##############################################################
def get_fname(patient, is_mask = False):
    fpath = os.path.join(FP_LGG, patient)
    if is_mask:
        pattern = "_([^_]*)_mask.tif$"
        fname = np.array([x for x in os.listdir(fpath) if "mask" in x])
    else:
        pattern = "_([^_]*).tif$"
        fname = np.array([x for x in os.listdir(fpath) if "mask" not in x])
    index = np.array([int(re.findall(pattern, x)[0]) for x in fname])
    idx = np.argsort(index)
    return fname[idx]

##############################################################
FP_LGG = "/data/Duke_BIOS824/LGG-segmentation/"
patients = [x for x in os.listdir(FP_LGG) if "TCGA" in x]    
patient = 'TCGA_CS_4941_19960909'

##############################################################
img_slice, img_mask = dict(), dict()

lst = get_fname(patient, is_mask = True)
img = [plt.imread(os.path.join(FP_LGG, patient, fname)) for fname in lst]
img_mask[patient]  = np.array(img)
    
lst = get_fname(patient, is_mask = False)
img = [plt.imread(os.path.join(FP_LGG, patient, fname)) for fname in lst]
img_slice[patient] = np.array(img)

##############################################################
fig, axes = plt.subplots(ncols=4, nrows=6, figsize = (2*4, 2*6))
axes = axes.ravel()

mask    = img_mask[patient]
num_img = mask.shape[0]

for idx in range(num_img):
    axes[idx].imshow(mask[idx])

plt.show()
#print(img_mask[patient].shape)

QStandardPaths: XDG_RUNTIME_DIR not set, defaulting to '/tmp/runtime-clint'
QXcbConnection: XCB error: 148 (Unknown), sequence: 178, resource id: 0, major code: 140 (Unknown), minor code: 20

Try using R

FP_LGG = "/data/Duke_BIOS824/LGG-segmentation/"
patient = "TCGA_CS_4941_19960909"
fname = paste0(patient, "_1", ".tif")
fpath = file.path(FP_LGG, patient, fname)
my_img <- bioimagetools::readTIF(fpath)

dim(my_img)

[1] 256 256   3   1

library(plotly)
mtcars$am[which(mtcars$am == 0)] <- 'Automatic'
mtcars$am[which(mtcars$am == 1)] <- 'Manual'
mtcars$am <- as.factor(mtcars$am)
p <- plot_ly(mtcars, x = ~wt, y = ~hp, z = ~qsec, color = ~am, colors = c('#BF382A', '#0C4B8E')) %>%
  add_markers() %>%
  layout(scene = list(xaxis = list(title = 'Weight'),
                     yaxis = list(title = 'Gross horsepower'),
                     zaxis = list(title = '1/4 mile time')))
print(p)

NULL